DBMS > Bangdb vs. Datomic vs. Microsoft Azure Synapse Analytics vs. NSDb vs. OpenSearch

System Properties Comparison Bangdb vs. Datomic vs. Microsoft Azure Synapse Analytics vs. NSDb vs. OpenSearch

Editorial information provided by DB-Engines

Name

Description

Converged and high performance database for device data, events, time series, document and graph

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

A distributed, RESTful search and analytics engine forked from Elasticsearch and based on Apache Lucene

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Time Series DBMS

Search engine

Secondary database models

Spatial DBMS

Vector DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	16.03
Rank	#37	Overall
	#4	Search engines

Website

bangdb.com

www.datomic.com

azure.microsoft.com/services/synapse-analytics

nsdb.io

github.com/opensearch-project
opensearch.org

Technical documentation

docs.bangdb.com

docs.datomic.com

docs.microsoft.com/azure/synapse-analytics

nsdb.io/Architecture

opensearch.org/docs/latest

Developer

Sachin Sinha, BangDB

Cognitect

Microsoft

Amazon Web Services

Initial release

2012

2016

2017

2021

Current release

BangDB 2.0, October 2021

1.0.7075, December 2023

2.5.0, January 2023

License

Commercial or Open Source

Open Source

BSD 3

commercial

limited edition free

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

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Implementation language

C, C++

Java, Clojure

C++

Java, Scala

Java

Server operating systems

Linux

All OS with a Java VM

hosted

Linux
macOS

All OS with a Java VM

Data scheme

schema-free

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

yes

yes: int, bigint, decimal, string

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

all fields are automatically indexed

yes

All search fields are automatically indexed

SQL

Support of SQL

SQL like support with command line tool

yes

SQL-like query language

APIs and other access methods

Proprietary protocol
RESTful HTTP API

RESTful HTTP API

ADO.NET
JDBC
ODBC

gRPC
HTTP REST
WebSocket

Java API
RESTful HTTP/JSON API

Supported programming languages

C
C#
C++
Java
Python

Clojure
Java

C#
Java
PHP

Java
Scala

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

Server-side scripts

Stored procedures

yes

Transaction Functions

Transact SQL

yes

Triggers

yes, Notifications (with Streaming only)

By using transaction functions

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

none

But extensive use of caching in the application peers

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

none

But extensive use of caching in the application peers

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

Using Apache Lucene

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes, run db with in-memory only mode

yes

recommended only for testing and development

User concepts

Access control

yes (enterprise version only)

yes

More information provided by the system vendor

Specific characteristics

OpenSearch is a highly scalable and extensible open-source software suite for search,...
» more

Competitive advantages

Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
» more

Typical application scenarios

The OpenSearch platform is used across a broad range of search , analytics, and observability...
» more

Licensing and pricing models

The OpenSearch Project offers open source software licensed under Apache License...
» more

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